The neuropathology of schizophrenia remains unclear. Some insight has come from modern
neuroimaging techniques, which offer an unparalleled opportunity to explore
in vivo
the structure
and function of the brain. Using functional magnetic resonance imaging, it has been found that the
large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the
temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered
network topology, with lower small-world index. The origin of these rsFC alterations and link with
the underlying structural connectivity remain unclear. In this work, we used a computational model
of spontaneous large-scale brain activity to explore the role of the structural connectivity in the
large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15
adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were
built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas.
Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from
other areas in proportion to the number of fibre tracts between them. The simulated mean field
activity was transformed into BOLD signal, and the properties of the simulated functional networks
were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not
directly linked to alterations in the structural topology. Instead, subtly randomized and less
small-world functional networks appear when the brain operates with lower global coupling, which
shifts the dynamics from the optimal healthy regime.